arXiv subjects

Yolanda Jiménez Teja

Publications and source records attributed to Yolanda Jiménez Teja.

2 recordsLinked to original sources

arXiv2026

J-PAS: unprecedented precision in stellar populations of diffuse tidal features

Galaxies frequently interact with nearby systems, a process that can significantly alter their morphology and star formation activity. However, spectroscopic studies of their faint and diffuse remnants require very long exposure times and often exceed the limited field of view of integral field units (IFUs). On the other hand, broad-band imaging can have a much wider field of view, but lacks the spectral resolution to identify key spectral features, restricting accurate constraints on stellar population properties. With its 54 narrow-band filters in the optical and wide coverage (planned 8000 square degrees), J-PAS fills this gap. In this case study, we examine PGC 3087775, a massive galaxy at z = 0.046179 (~ 201 Mpc) in the later stages of a major merger in the J-PAS early data release. Photometry was validated with MaNGA IFU data (for the central part). Stellar population properties was derived using both J-PAS and SDSS photometry. SDSS indicates a metal-rich population with an extended star formation history (SFH) and elevated star formation rates. J-PAS instead points to a less metal-rich population with moderate extinction and a more rapid SFH, consistent with a quenched stellar population. The average Dn(4000) index of the tidal features is 1.24, suggesting that it was a non-dry merger and a fourfold improvement in the precision of stellar mass and Dn (4000) was found with J-PAS. We also assessed two heuristic methods for estimating the mass-to-light ratio from SDSS filters and found that they overestimate the stellar mass in this galaxy by 0.5 dex and 0.4 dex relative to SED fitting results from J-PAS and SDSS, respectively. Future work will extend this analysis to a larger sample of merging galaxies and evolution of the stellar populations of such structures across the nearby Universe to unprecedented detail. This project is fully reproducible, through Maneage (commit 0f0d7e2).

astro-ph.GA↗

arXiv2021

J-PLUS: Searching for very metal-poor star candidates using the SPEEM pipeline

We explore the stellar content of the Javalambre Photometric Local Universe Survey (J-PLUS) Data Release 2 and show its potential to identify low-metallicity stars using the Stellar Parameters Estimation based on Ensemble Methods (SPEEM) pipeline. SPEEM is a tool to provide determinations of atmospheric parameters for stars and separate stellar sources from quasars, using the unique J-PLUS photometric system. The adoption of adequate selection criteria allows the identification of metal-poor star candidates suitable for spectroscopic follow-up. SPEEM consists of a series of machine learning models which uses a training sample observed by both J-PLUS and the SEGUE spectroscopic survey. The training sample has temperatures Teff between 4\,800 K and 9\,000 K; $\log g$ between 1.0 and 4.5, and $-3.1<[Fe/H]<+0.5$. The performance of the pipeline has been tested with a sample of stars observed by the LAMOST survey within the same parameter range. The average differences between the parameters of a sample of stars observed with SEGUE and J-PLUS, which were obtained with the SEGUE Stellar Parameter Pipeline and SPEEM, respectively, are $ΔTeff\sim 41$ K, $Δ\log g\sim 0.11$ dex, and $Δ[Fe/H]\sim 0.09$ dex. A sample of 177 stars have been identified as new candidates with $[Fe/H]<-2.5$ and 11 of them have been observed with the ISIS spectrograph at the William Herschel Telescope. The spectroscopic analysis confirms that $64\%$ of stars have $[Fe/H]<-2.5$, including one new star with $[Fe/H]<-3.0$. SPEEM in combination with the J-PLUS filter system has shown the potential to estimate the stellar atmospheric parameters (Teff, $\log g$, and [Fe/H]). The spectroscopic validation of the candidates shows that SPEEM yields a success rate of $64\%$ on the identification of very metal-poor star candidates with $[Fe/H]<-2.5$.

astro-ph.SR↗